Celigo Inc., maker of an integration platform-as-a-service, today introduced new capabilities aimed at simplifying how enterprises build and scale up artificial intelligence-driven automation.

The Redwood City, California-based company announced Celigo Ora, a natural-language interface, along with a new Agent Builder tool to enable non-technical users to create and manage complex workflows across enterprise systems. The company said the additions are aimed at helping organizations move AI initiatives from pilots into production.

Celigo Ora allows users to design, modify and troubleshoot integrations using conversational prompts rather than code. The interface is powered by a network of specialized AI agents that understand business systems, workflows and data context, enabling users to execute tasks such as building workflows or resolving errors without submitting information technology department tickets.

Agent Builder complements Ora by providing a low-code environment for developing AI-driven automations that can reason through tasks and act across systems. The tools are integrated with Celigo’s Model Context Protocol server to provide secure connectivity between AI agents and enterprise applications.

The company said the combined offering allows organizations to manage a automation scenarios ranging from rules-based processes to adaptive AI agents within a single platform while maintaining IT-led governance controls such as auditability and human-in-the-loop approvals.

“Any team can now describe what they need to put into production, from simple integrations to autonomous agents, while IT maintains the control and governance the enterprise requires,” Matt Graney, Celigo’s chief product officer, said in a statement.

The announcement reflects a broader challenge facing enterprises as they attempt to operationalize AI. According to Celigo-sponsored research conducted by MIT Technology Review Insights, only 1% of organizations without a unified integration strategy have scaled AI beyond a single department. In contrast, 90% of companies with production AI workflows already use an integration platform.

Celigo said that gap highlights the importance of the underlying infrastructure beyond model capabilities alone in determining whether AI initiatives succeed at scale. Many organizations remain stuck in early-stage pilots due to fragmented systems and a lack of standardized integration frameworks.

The company said it addresses that issue by providing a standardized way to connect AI agents to enterprise systems while enforcing governance policies.

Celigo Ora is currently available in a beta test, while Agent Builder and the MCP server are generally available.

Image: Pixabay